Inverse giant magnetoresistance found in thin-film device
Researchers fabricated and characterized a new magnetoresistive device that may one day find future spintronics applications. Iron nitride (Fe4N) has attracted interest among materials scientists due to its large spin-asymmetric conductance, as well as a large negative spin polarization. The negative spin polarization is of particular interest because it controls the magnetoresistance ratio, a measure of the resistance due to magnetic field effects, important for designing tunnel magnetoresistant (TMR) devices, widely used in the read-heads of modern day hard disk drives.
The damping constant of Fe4N in the 001 orientation, measured for the first time, is comparable with other soft magnetic materials. It is an important parameter for spintronic materials, playing a vital role in determining the critical current needed for inducing magnetization switching.
Using a target-facing-target reactive sputtering system, the researchers created a multilayer device consisting of a total of eight different layers. From top to bottom, the layers are made up of ruthenium, silver, iron, silver, Fe4N, silver, iron and magnesium oxide. The stack was then further processed using electron beam lithography and ion beam etching. The final multilayer device is a giant magnetoresistant (GMR) device shaped as a roughly 90-nanometer-high column with an elliptical cross section, 160 nanometers in diameter at its widest.
Contrary to most GMR devices, their new device exhibits an inverse GMR behavior, meaning it creates a higher resistance when the magnetization between the Fe4N and its neighboring layers is parallel, and lower when antiparallel.
This somewhat novel property has been observed before, but is a first for a material with such large spin polarization, making it more likely to be practical for potential applications, possibly as a new component for next-generation spintronic devices.
Source: “Damping constant measurement and inverse giant magnetoresistance in spintronic devices with Fe4N,” by Xuan Li, Hongshi Li, Mahdi Jamali, and Jian-Ping Wang, AIP Advances (2017). The article can be accessed at https://doi.org/10.1063/1.4994972 .